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Novel immune‐related signature for risk stratification and prognosis in prostatic adenocarcinoma

A substantial proportion of prostatic adenocarcinoma (PRAD) patients experience biochemical failure (BCF) after radical prostatectomy (RP). The immune microenvironment plays a vital role in carcinogenesis and the development of PRAD. This study aimed to identify a novel immune‐related gene (IRG)‐bas...

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Detalles Bibliográficos
Autores principales: Zhao, Hai‐Bo, Zeng, Yan‐Ru, Han, Zhao‐Dong, Zhuo, Yang‐Jia, Liang, Ying‐Ke, Hon, Chi Tin, Wan, Song, Wu, Shulin, Dahl, Douglas, Zhong, Wei‐De, Wu, Chin‐Lee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486177/
https://www.ncbi.nlm.nih.gov/pubmed/34252262
http://dx.doi.org/10.1111/cas.15062
Descripción
Sumario:A substantial proportion of prostatic adenocarcinoma (PRAD) patients experience biochemical failure (BCF) after radical prostatectomy (RP). The immune microenvironment plays a vital role in carcinogenesis and the development of PRAD. This study aimed to identify a novel immune‐related gene (IRG)‐based signature for risk stratification and prognosis of BCF in PRAD. Weighted gene coexpression network analysis was carried out to identify a BCF‐related module in a discovery cohort of patients who underwent RP at the Massachusetts General Hospital. The median follow‐up time was 70.32 months. Random forest and multivariate stepwise Cox regression analyses were used to identify an IRG‐based signature from the specific module. Risk plot analyses, Kaplan‐Meier curves, receiver operating characteristic curves, univariate and multivariate Cox regression analyses, stratified analysis, and Harrell’s concordance index were used to assess the prognostic value and predictive accuracy of the IRG‐based signature in the internal discovery cohort; The Cancer Genome Atlas database was used as a validation cohort. Tumor immune estimation resource database analysis and CIBERSORT algorithm were used to assess the immunophenotype of PRAD. A novel IRG‐based signature was identified from the specific module. Five IRGs (BUB1B, NDN, NID1, COL4A6, and FLRT2) were verified as components of the risk signature. The IRG‐based signature showed good prognostic value and predictive accuracy in both the discovery and validation cohorts. Infiltrations of various immune cells were significantly different between low‐risk and high‐risk groups in PRAD. We identified a novel IRG‐based signature that could function as an index for assessing tumor immune status and risk stratification in PRAD.